Genetic Algorithms Multi-Objective Model for Project Scheduling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33126
Genetic Algorithms Multi-Objective Model for Project Scheduling

Authors: Elsheikh Asser

Abstract:

Time and cost are the main goals of the construction project management. The first schedule developed may not be a suitable schedule for beginning or completing the project to achieve the target completion time at a minimum total cost. In general, there are trade-offs between time and cost (TCT) to complete the activities of a project. This research presents genetic algorithms (GAs) multiobjective model for project scheduling considering different scenarios such as least cost, least time, and target time.

Keywords: Genetic algorithms, Time-cost trade-off.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1097291

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2332

References:


[1] Liu, L., Burns, S., and Feng, C., “Construction Time-Cost Trade-Off Analysis Using LP/IP Hybrid Method,” Journal of Construction Engineering and Management, ASCE, 121(4), 446-454, 1995.
[2] Maghrebi, M., Afshar, A., and Maghrebi, M. J., “A Novel Mathematical Model for Deterministic Time-cost Trade-off Based on Path Constraint,” International Journal of Construction Engineering and Management 2(5): 137-142, 2013.
[3] Zheng, D., Ng, S. T., and Kumaraswamy, M., “Applying a Genetic Algorithm-Based Multiobjective Approach for Time-Cost Optimization,” Journal of Construction Engineering and Management, ASCE, 130(2), 168-176, 2004.
[4] Forrest, S., “Genetic Algorithms: Principles of Natural Selection Applied to Computation”, Science 261, 1993.
[5] Feng, C., Liu, L., and Burns, S., “Using genetic algorithms to solve construction time–cost trade-off problems,” ASCE Journal of Computing in Civil Engineering, 11(3), 184–189, 1997.
[6] Li, H., Cao, J.-N., and Love, P., “Using Machine Learning and GA to Solve Time-Cost Trade-Off Problems,” Journal of Construction Engineering and Management, ASCE, 125(5), 347-353, 1999.
[7] Hegazy, T., “Optimization of construction time–cost trade-off analysis using genetic algorithms,” Canadian Journal of Civil Engineer Vol. 26, 685–697, 1999.
[8] Ammar, M. A., “Optimization of project time-cost trade-off problem with discounted cash flows,” Journal of Construction Engineering and Management, 137(1), 65-71, 2010.
[9] Aghassi, H., et al., “a multi-objective Genetic Algorithm for optimization time-cost trade-off scheduling,” Knowledge Technology, Springer, 356-359, 2012.
[10] Ghoddousi, P., et al., “Multi-mode resource-constrained discrete time– cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm,” Automation in Construction, 216–227, 2013.
[11] Bettemir, Ö.H., “Experimental Design for Genetic Algorithm Simulated Annealing For Time Cost Trade-Off Problems,” International Journal of Engineering & Applied Sciences (IJEAS) Vol.3, Issue 1, 15-26, 2011.